age. Additionally, the main predictors of HGS were assessed for each BMI tertile. In primary malnutrition (T1), the main predictor of HGS was body weight, whereas in the other two tertiles (T2, T3), the PhA was the main predictor of HGS.In this work, a sand and dust storm vulnerability mapping (SDS-VM) approach is developed to model the vulnerability of urban blocks to SDS using GIS spatial analysis and a range of geographical data. The SDS-VM was carried out in Ahvaz, IRAN, representing one of the most dust-polluted cities in West Asia. Here, vulnerability is defined as a function of three components exposure, sensitivity, and adaptive capacity of the people in the city blocks to sand and dust storms. These components were formulated into measurable indicators (i.e. GIS layers) including PM2.5, wind speed, distance from dust emission sources, demographic statistics (age, gender, family size, education level), number of building floors, building age, land surface temperature (LST), land use, percentage of literate population, distance from health services, distance from city facilities (city center, shopping centers), distance from infrastructure (public transportation, main roads and highways), distance from parks and green spaces, and green area per capita. The components and the indicators were weighted using analytical hierarchy process (AHP). Different levels of risks for the components and the indicators were defined using ordered weighted averaging (OWA). Urban SDS vulnerability maps at different risk levels were generated through spatial multi-criteria data analysis procedure. Vulnerability maps, with different risk levels, were validated against field-collected data of 781 patients hospitalized for dust-related diseases (i.e. respiratory, cardiovascular, and skin). Results showed that (i) SDS vulnerability map, obtained from the developed methodology, gives an overall accuracy of 79%; (ii); regions 1 and 5 of Ahvaz are recognized with the highest and lowest vulnerabilities to SDS, respectively; and (iii) ORness equal to 0 (very low risk) is the optimum SDS-VM risk level for decision-making to mitigate the harmful impacts of SDS in the deposition areas of Ahvaz city.Numerous pieces of evidence documented the importance of gut microbiota in regulating human health and evaluating the toxicity of environmental pollutants, which are closely related to the host health in various aspects, including nutrition, energy translation, metabolism, pathogen resistance, and immune function. A variety of environmental factors can disrupt gut microbiota and their functions, and inevitably cause immune diseases, obesity and diabetes. However, deciphering the inner mechanisms involved in the functional interaction of gut microbes with host health is still needed extensive investigations. This review focused on the essential roles of intestinal microbes in host-related diseases and highlighted the development and applications of germ-free (GF) animal models, mainly zebrafish. Moreover, the generation, immunity characters, advantages and challenges of GF zebrafish models were also summarized. Importantly, the composition and isolation of zebrafish gut bacteria for further application and toxicity evaluation of aquatic environmental pollutants were also discussed. In conclusion, GF zebrafish play irreplaceable roles in understanding the potential functions and responses of customized microbiota towards human and environmental health implications.Inoculation of soil or seeds with plant growth promoting bacteria ameliorates metal toxicity to plants by changing metal speciation in plant tissues but the exact location of these changes remains unknown. Knowing where the changes occur is a critical first step to establish whether metal speciation changes are driven by microbial metabolism or by plant responses. Since bacteria concentrate in the rhizosphere, we hypothesised steep changes in metal speciation across the rhizosphere. We tested this by comparing speciation of zinc (Zn) in roots of Brassica juncea plants grown in soil contaminated with 600 mg kg-1 of Zn with that of bulk and rhizospheric soil using synchrotron X-ray absorption spectroscopy (XAS). Seeds were either uninoculated or inoculated with Rhizobium leguminosarum bv. trifolii and Zn was supplied in the form of sulfide (ZnS nanoparticles) and sulfate (ZnSO4). Consistent with previous studies, Zn toxicity, as assessed by plant growth parameters, was alleviated in B. juncea inoculated with Rhizobium leguminosarum. XAS results showed that in both ZnS and ZnSO4 treatments, the most significant changes in speciation occurred between the rhizosphere and the root, and involved an increase in the proportion of organic acids and thiol complexes. https://www.selleckchem.com/products/oxalacetic-acid.html In ZnS treatments, Zn phytate and Zn citrate were the dominant organic acid complexes, whilst Zn histidine also appeared in roots exposed to ZnSO4. Inoculation with bacteria was associated with the appearance of Zn cysteine and Zn formate in roots, suggesting that these two forms are driven by bacterial metabolism. In contrast, Zn complexation with phytate, citrate and histidine is attributed to plant responses, perhaps in the form of exudates, some with long range influence into the bulk soil, leading to shallower speciation gradients.It is still a great challenge to address nutrient pollution issues caused by various point sources and non-point sources on the watershed scale. Source contribution analysis based on watershed modeling can help watershed managers identify major pollution sources, propose effective management plans and make smart decisions. This study demonstrated a technical procedure for addressing watershed-scale water pollution problems in an agriculture-dominated watershed, using the Dengsha River Watershed (DRW) in Dalian, China as an example. The SWAT model was improved by considering the constraints of soil nutrient concentration, i.e., nitrogen (N) and phosphorus (P), when modeling the nutrient uptake by a typical crop, corn. Then the modified SWAT model was used to quantify the contributions of all known pollution sources to the N and P pollution in the DRW. The results showed that crop production and trans-administrative wastewater discharge were the two dominant sources of nutrient pollution. This study further examined the responses of nutrient loss and crop yield to different fertilizer application schemes.